Deep Learning in Object Detection for the Autonomous Car

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This chapter explores the practical application of artificial intelligence (AI) techniques in self-driving cars, mainly focusing on object recognition. Deep learning has emerged as a powerful tool for object detection, playing a crucial role in processing data from lidar, radar, and video cameras. These three technologies are essential components of autonomous vehicles, providing critical obstacle information that enables the automatic system to execute appropriate actions based on the received data. We delve into three advanced techniques that enhance object detection capabilities in autonomous cars: PointPillars for Lidar, Convolutional Neural Networks (CNNs) for radar, and You Only Look Once (YOLO) for video cameras. PointPillars is a state-o- -the-art technique that efficiently processes lidar point cloud data to detect objects, offering high accuracy and real-time performance. This method transforms point cloud data into a structured format that is easier for neural networks to process, facilitating rapid and accurate object detection. For radar, Convolutional Neural Networks (CNNs) are employed to leverage their strength in processing grid-like data structures. CNNs can effectively handle the spatial information captured by radar sensors, enabling precise detection and classification of objects, even in challenging conditions such as poor visibility or adverse weather. In video camera applications, the YOLO (You Only Look Once) algorithm is utilized for its ability to detect and classify multiple objects within a single frame quickly. YOLO's real-time detection capability and high accuracy make it an ideal choice for video-based object detection in self-driving cars. This chapter provides a comprehensive overview of these cutting-edge deep learning techniques, demonstrating their pivotal role in advancing the object recognition capabilities of autonomous vehicles. Through detailed discussions and examples, we highlight how these methods contribute to the development of safer and more reliable self-driving car systems.